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Biological Data Analysis - Statistician

European Molecular Biology Laboratory (EMBL)

Location: Heidelberg - Germany
Salary: (Grade 5-6)
Hours: Full Time
Contract Type: Fixed-Term/Contract
Placed On: 18th February 2020
Closes: 12th April 2020
Job Ref: HD01705

About the team/job

You will

  • Be part of a team that provides data science and bioinformatics support to EMBL researchers, as a specialist for statistical methodology.
  • Provide statistical consulting on biological data analysis, experimental design, statistically sound interpretation and scientific presentation of results.
  • Provide training (2-5 days courses) in the area of computational statistics and data science in biology.

EMBL is an international research organization covering many fields of modern biology, where dataset sizes are doubling every 18 months. EMBL’s data science centre provides expertise, advice, hands-on collaboration and training for scientists across EMBL, and is searching for an applied statistician. The position will be co-affiliated with the research group of Wolfgang Huber (

The consultancy engagements typically range all the way from brief high-level methodological advice to in-depth collaborations and solving novel statistical challenges emerging from new research data, methods and technologies. The emphasis of the position is on providing excellent service, in addition, it offers opportunities to make own research contributions.  

The job holder will be expected to collaborate and interact with many scientists across EMBL and also with partner networks (Elixir, de.NBI). EMBL offers an international, interdisciplinary, and highly collaborative work environment.

You have

  • A PhD or higher education degree (e.g., MSc) and relevant work experience in statistics or bioinformatics with solid theoretical foundations in probability and applied statistics
  • Programming skills in R
  • Strong interest in computational statistics, open science and good scientific practice
  • Experience in teaching
  • Experience in biostatistical consultin
  • Good communication skills in written and spoken English
  • Basic experience in analysis of high-throughput biological data (genomics, transcriptomics, epigenetics, proteomics, etc.)
  • An interest in cutting-edge molecular biology and its data-generating technologies

You might also have

  • Experience in analyzing next-generation sequencing (NGS), imaging, proteomics, or microfluidics data sets
  • Experience in R as a package developer or maintainer
  • Knowledge of Python or other scripting languages
  • Knowledge of scientific authoring frameworks (LaTeX, Rmarkdown) and R-Shiny would be considered a plus
  • Experience with version control, method benchmarking, or data management technologies


You enjoy team science and are enthusiastic about contributing your skills in a world-class research environment. EMBL holds the world’s most widely used biodata repositories and is one of the largest producers of data in molecular biology, and advancing data sciences is very much within the spirit of the institution. The advertised position also offers the opportunity to help shape future developments of data science and open science in biology, such as publication and communication best practices. 

Why join us

EMBL is an inclusive, equal opportunity employer offering attractive conditions and benefits appropriate to an international research organisation with a collegial and family-friendly working environment. The remuneration package comprises a competitive salary, a comprehensive pension scheme, medical, educational and other social benefits, as well as financial support for relocation and installation, including your family and the availability of an excellent child care facility on campus. EMBL has a large thriving community of bioinformaticians, working in close collaboration with experimental scientists and with strong links to other local and international scientists and institutions.

For additional information and the instruction on how to apply, please click the Apply button above.

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